chore: moved presenting functions to Present_data.py

Present_data.py

@@ -0,0 +1,26 @@
+from Handle_emg_data import *
+from Signal_prep import *
+
+# PLOT FUNCTIONS:
+
+# Plots DataFrame objects
+def plot_df(df:DataFrame):
+    lines = df.plot.line(x='timestamp')
+    plt.show()
+
+# Plots ndarrays after transformations 
+def plot_arrays(N, y):
+    plt.plot(N, np.abs(y))
+    plt.show()
+
+
+# DATA FUNCTIONS
+
+def get_data()
+    
+
+
+
+def main():
+
+    return None

Signal_prep.py

@@ -83,15 +83,3 @@ def denoice_dataset(handler:Handler.CSV_handler, subject_nr, which_arm, round, e
     return df_new
 
 
-
-# MOVE TO Present_data.py
-# Plots DataFrame objects
-def plot_df(df:DataFrame):
-    lines = df.plot.line(x='timestamp')
-    plt.show()
-
-# Plots ndarrays after transformations 
-def plot_arrays(N, y):
-    plt.plot(N, np.abs(y))
-    plt.show()
-

Test_functions.py

@@ -50,7 +50,7 @@ def test_plot_wavelet_both_ways():
     #print(len(cA_filt))
     y_new_values = inverse_wavelet(df, cA_filt, cD_filt)
     #print(len(y_new_values))
-    plot_arrays(N, y_new_values)
+    #plot_arrays(N, y_new_values)
 
 def test_soft_load_func():
     handler = CSV_handler()
@@ -70,7 +70,7 @@ def test_total_denoising():
     
 
     # Denoised df:
-    df_denoised = denoice_dataset(handler, 3, 'left', 3, 3, 0.2)
+    df_denoised = denoice_dataset(handler, 3, 'left', 3, 3, 0.7)
     print(df_denoised.head)
 
     x = get_xory_from_df('x', df)
@@ -83,3 +83,4 @@ def test_total_denoising():
     plt.show()
 
 test_total_denoising()
+#test_plot_wavelet_both_ways()